Helping New Yorkers Discover, Understand, and Explore Diverse Cuisines

Ideally, restaurant owners should offer detailed information about their dishes and opportunities to learn about their cuisines. However, depending on owner participation can limit the database's completeness. Additionally, gathering information from the public rather than owners can make it more objective, reliable, and free from promotional bias.

We conducted user interviews to explore how New Yorkers try new foods, focusing on young adults because they dine out more frequently than older age groups. According to a 2016 Gallup survey, 72% of young adults (ages 18-34) reported eating dinner at a restaurant in the past week, compared to 65% of middle-aged adults (ages 35-54) and 50% of older adults (ages 55+). Data by Gallup, 2016

We researched 3 types of competitors: food, crowdsourcing, and game/social media by lightning demo and competitive analysis. The reason why we checked crowdsourcing apps is that they are strong at collecting data from users. We looked at engaging game/social media apps to get inspiration on gamification to encourage users to submit menu data.

Food

Opportunities:

Cultural aspect of dining

Objective & exhaustive menu information

Crowdsourcing

Keys to create a community:

Mutual passion/motivation

Small rewarding features that encourage posting

Spatial Game/Social Media

Keys for engagement:

Playfulness and cuteness

Interactive elements on map (avatars, images, characters, and heat maps)

We brainstormed using Crazy 8s, MoSCoW, and SCAMPER methods. There are already many popular, well-designed food apps in the market, so we wanted to create new value that differentiates us from existing apps. (It was hard...!)

We created mid-fidelity wireframes, followed by high-fidelity prototypes, and used them for testing. In the test, we aimed to pick up a cuisine that our participants have never tried to see how they learn about new cuisine.

SCENARIO & TASK

Try Egyptian cuisine

With diet preference (vegetarian, prefers spicy food)

Testing core features

METHODOLOGY

In-person and remote

Moderated testing

PARTICIPANTS

5 participants

Young adults

NYC residents

In the testing, participants mentioned the content is too text-heavy and they wanted to less text. In order to solve this issue, we used "See more" buttons and hide texts when they open the page. In addition, we replaced the bulleted ingredient list with list with image to help users process information and make content more engaging.

Problem

The content, especially the menu description is text-heavy.

Solution

Use tags instead of the bulleted list, and reduce the amount of texts disclosed at once.

The original design asked users to provide taste feedback on dishes using a 1 to 5 scale. However, users mentioned that taste is subjective, so they doubted the accuracy of the data. That’s why I replaced the 1 to 5 scale with on/off tags to simplify the review method. This way, we can reduce the influence of personal taste preferences.

Problem

A 1-to-5 feedback on taste is subjective and not reliable.

Solution

Use taste tags instead to describe the dish on the review page.

More than half of users stated they wanted to interact with the map. They also pointed out the lack of engaging features on it. In order to make the map engaging and interactive, I added flag icons for the restaurants, showed the recent review photos, saved places, and an avatar.

Problem

The map does not provide enough interactivity and engaging experience.

Solution

Provide more visual and personal elements on the map.

The challenging and exciting part of this project was to differentiate our design from existing apps. There are many good restaurant search/food-related products in the market, so coming up with the features the existing apps are missing was difficult. Through the process of dealing with this difficulty, I learned that indirect competitors and unrelated apps could be helpful sources of inspiration. Also, I could understand the importance of iterating the design process to polish the ideas.

As a next step, I would like to enhance the process of registering new restaurant and menu data for our crowdsourcing app, as this master data is crucial for collecting reviews.

Also, currently, our user flow is primarily designed for users who are interested in specific cuisines. I want to introduce personalized suggestion features to encourage users to explore and try new cuisines they haven't even considered before.

Finally, I would like to expand the information available to users to help them understand a dish and decide if it's worth trying. We've so far included ingredients, taste tags, and authenticity, but I'm interested in exploring other options as well.